Welcome to the very first edition of AIFN Insights!

I am excited to have you join me on this journey. When I wrote “AI-First Nation”, I wanted to share Singapore’s unique approach to AI adoption and talent development. But I realized that a book, while comprehensive, can’t keep pace with the rapidly evolving AI landscape and the continuous learning from our work at AI Singapore.

That is why I am launching this weekly newsletter – to share practical insights, strategies, and lessons learned from our ongoing mission of transforming Singapore into an AI-First nation. Drawing on insights from our work with over 500 companies, training over 400 AI engineers, and applying AI across various industries, I will offer practical advice and/or the latest interesting AI technology each week.

Whether you are a business leader planning your AI strategy, a professional looking to enhance your career with AI capabilities, or simply someone interested in AI adoption, I promise to deliver valuable insights that you can apply immediately.

In this inaugural edition, I want to share one of our most successful strategies – one that challenged conventional wisdom about AI talent development and created a sustainable pipeline of AI engineers for Singapore…

This Week’s Big Idea: The Blue Ocean Strategy That Built AI Singapore’s AI Talent Pipeline

In June 2017, we faced what seemed like an impossible challenge. AI Singapore was tasked to help 100 companies build AI products and solutions through our 100E program. But where would we find the AI talent? We started with just four AI engineers, and when we advertised for more, out of 300 resumes, only ten were from Singaporeans.

Being a government-funded programme hosted by a local university, our salary structure couldn’t compete with tech giants like Google, Microsoft, Grab, and Facebook. We needed a different approach. Here’s how we solved it:

Creating Our Blue Ocean

Instead of competing in the “red ocean” of computer science graduates, we launched the AI Apprenticeship Programme (AIAP) in 2018 with just two criteria:

• Must be a Singapore citizen
• Pass the AIAP technical test and interview

What didn’t we deliberately ask for? Computer science degrees or AI specializations. We looked where others weren’t. We hunted for passionate individuals who:

• Self-taught themselves Python and AI/ML libraries
• Participated in MOOCs or Kaggle competitions
• Had strong domain expertise and loved working with data

The Real-World Difference

Our apprentices didn’t work with toy datasets. They built and deployed AI models end-to-end (data ingestion, cleaning, model training, tunning and deployment) for actual “paying” customers, facing real challenges:

• Working with demanding stakeholders
• Missing or limited datasets
• Changing user requirements
• Integration with existing systems

Completed projects are often delivered in containers and AI/ML models are often exposed via APIs. So, Python code (sometimes C/C++, Java etc). Never a Jupyter notebook!

As one pioneer apprentice, who joined the defence industry upon graduation, said: 

The results?

Extraordinary!

• Over 70% of our apprentices secured AI/ML/Data jobs before completing the 9-month programme. With more than 90% landing a role within 3-months of graduation.
• Only 21% of our successful apprentices were computer science graduates. That meant we were able to help nearly 80% of non-computer science/engineering graduates transition to become an AI Engineer. Many of them come from economics, psychology, business, biology, and engineering.

Actionable Takeaway for Organizations

When building your AI team:

1. Look beyond traditional credentials
2. Value domain expertise and learning ability
3. Create opportunities for hands-on experience
4. Focus on problem-solving capabilities

Today, this blue ocean strategy has transformed over 400 professionals into AI engineers and data scientists, creating a sustainable talent pipeline for AI Singapore’s AI engineering talent requirements, with those whom we are not fortunate enough to retain, will join the AI industry in Singapore.

Coming Next:”The 5 Pillars of AI Readiness” – I’ll share our framework for assessing if your organization is truly ready for AI adoption.

Building an AI-First Nation together, Laurence

P.S. Interested in joining our next AIAP cohort? Visit AIAP.SG to learn more.